JP5053215B2 - Image processing apparatus, image processing method, and program - Google Patents

Description

  The present invention relates to a technique for correcting the tone of a monochrome image.

  Manga is a typical monochrome line drawing. Manga is generally a monochrome line drawing with a unique Japanese texture, unlike Western comics (Comic). In other words, in manga, the expression of gradation (color shade) and the emotions of characters are mainly expressed by halftone dots of various patterns, solid lines, effect lines, contour lines, and other drawing lines. It is very different in nature from comics that have many.

  Conventionally, manga is printed on paper and supplied to the market. However, for reasons such as the cost of color printing being too high, all but the first color pages of magazines and the like have been produced only in monochrome.

  However, with the development of communication technology of terminal devices such as mobile phones, the number of sites where digitalized manga can be subscribed via a communication line has increased rapidly, and the opportunity to view manga on a liquid crystal monitor or the like has increased. Along with this, there is an increasing demand for manga that has been colored (colored and colored). Also, since there is no monochrome manga culture outside Japan, it is necessary to color monochrome manga in order to expand the manga business overseas.

  Here, in manga colorization work, an operator may directly color an analog image written on paper (or printed) with a color pen or the like, but the analog image is read with a scanner or the like. As a result, the operator often performs coloring processing using a computer.

  At the time of digitization, an obtained digital image may include an offset value (such as a noise component) that is not intended by the operator due to the influence of paper quality, scanner performance, and the like. Therefore, for coloring, a worker performs preprocessing for removing noise from image data. Specifically, image tone correction (color balance adjustment, resetting of shadow points and highlight points, etc.) is executed.

  In addition to the purpose of the above-described coloring process, for example, when a monochrome digital image is simply supplied or a digital image is acquired from an analog image published in the past, In some cases, a digital image acquired from an image using a scanner or the like is subjected to color correction.

  By the way, when the color correction is performed manually by the operator, the determination of the reading state of the digital image is performed based on the subjectivity of the operator. In addition, since the worker performs the work manually, there is a problem that it takes time for image processing. Thus, a technique for automating color tone correction in accordance with the image reading state has been proposed (for example, Patent Document 1).

  In Patent Document 1, first, with respect to image data acquired by pre-scanning, an average density value of selected pixels and a density variation (standard deviation) around each selected pixel are obtained for each selected pixel. Then, based on the frequency distribution (histogram) of the pixels of each gradation obtained by weighting the weighting value determined according to the variation and the average density value, the reference point of the highlight point and the shadow point is set. .

  According to this technique, by appropriately setting the weighting value, it is possible to suppress highlight points and shadow points from being inappropriately selected from the entire image, and thus color tone correction can be performed with high accuracy. .

  In addition to Patent Document 1, commercially available image processing software has a function of automatically correcting color tone (level correction) according to a predetermined algorithm based on histograms such as luminance information and RGB information.

JP-A-11-55517

  However, in the technique described in Patent Document 1, it is necessary to pre-scan a large number of samples (for example, about 50 to 100 sheets) in advance in order to set the reference points for highlight points and shadow points with high accuracy. There was a risk that work efficiency would decrease. In addition, there is a possibility that quality may vary depending on the sample to be pre-scanned.

  In particular, monochrome images such as line drawings including manga have properties different from those of natural images, such as the appearance frequency of each pixel being particularly high in the drawing color and the background color. For this reason, the above-described image processing software, which excels in color tone correction of natural images, cannot obtain a sufficient effect when a monochrome image is processed, and the operator has to perform manual adjustment. Therefore, it takes a long time to correct the color tone, and there is also a possibility that individual differences may occur in the quality after the color tone correction.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to provide a technique for performing color tone correction of a monochrome image with high accuracy and high efficiency.

In order to solve the above-described problems, the invention of claim 1 is an image processing apparatus for adjusting the contrast of a monochrome image, based on the monochrome image, acquisition means for acquiring monochrome image data in multi-tone representation, and the monochrome image Thus, a pixel set having a gradation value (0 to TMb, TMw to 255) within a predetermined gradation range with respect to the specific gradation value (0, 255) corresponding to the specific color is specified as a solid area of the specific color. With the specific means and the specific gradation value (0, 255) as an initial threshold value, the threshold value is increased or decreased to be extracted from the solid area of the monochrome image by binarization using the threshold value. The threshold value when the area of the pixel set (S (Tb), S (Tw)) satisfies a predetermined area criterion is determined based on the comparison with the area (Sb, Tw) of the solid region, and the threshold value the correction threshold (D b, a correction threshold acquisition means for acquiring as DTw), the correction threshold value (DTb, the tone value of DTw), by resetting the particular gradation value (0, 255), said monochrome image And a contrast adjusting means for adjusting contrast.

  The invention of claim 2 is the image processing apparatus according to the invention of claim 1, further comprising smoothing means for generating a smoothed image by spatially smoothing the monochrome image, The specifying means specifies the solid region based on the smoothed image.

  The invention according to claim 3 is the image processing apparatus according to claim 1 or 2, wherein the specifying unit specifies an area obtained by further shrinking the pixel set of the gradation value as the solid area. It is characterized by.

According to a fourth aspect of the present invention, there is provided the image processing apparatus according to any one of the first to third aspects, wherein the specifying unit is configured to generate a gradation value corresponding to a drawing color based on the monochrome image. In addition, the pixel set having the gradation value within the predetermined gradation range is specified as the first solid area, and the pixel set having the gradation value within the predetermined gradation range with respect to the gradation value corresponding to the background color is specified as the second solid area. The correction threshold value acquisition unit acquires the first correction threshold value and the second correction threshold value as the correction threshold value for each of the first solid region and the second solid region of the monochrome image. The contrast adjusting means adjusts the contrast of the monochrome image based on the first correction threshold and the second correction threshold.

  The invention of claim 5 is the image processing apparatus according to the invention of claim 4, wherein the specifying means analyzes the frequency distribution of pixels of each gradation value of the monochrome image to obtain a drawing color level. The first solid area and the second solid area are specified based on a solid area specifying threshold acquired from each of the gradation side and the gradation side of the background color.

  The invention of claim 6 is the image processing apparatus according to the invention of claim 5, wherein the specifying unit is configured to calculate the intermediate gradation between the gradation of the drawing color and the gradation of the background color. A first gradation value that is biased by a predetermined number of classes to the gradation side of the background color with respect to the gradation value having the highest appearance frequency on the gradation side of the drawing color, and the background color from the intermediate gradation Each of the second gradation value that is biased by a predetermined number of classes to the gradation side of the drawing color with respect to the gradation value having the highest appearance frequency on the gradation side is set as the solid area specifying threshold. It is characterized by that.

  The invention according to claim 7 is the image processing apparatus according to any one of claims 1 to 6, wherein the specifying means detects an edge portion having a predetermined pixel width in the entire area of the monochrome image. The solid area is identified from the remaining residual area.

The invention of claim 8 is an image processing method for adjusting the contrast of a monochrome image, comprising: (a) acquiring monochrome image data in multi-tone representation; and (b) the step (a). Based on the monochrome image acquired in this way, a pixel set having gradation values (0 to TMb, TMw to 255) within a predetermined gradation range with respect to a specific gradation value (0, 255) corresponding to a specific color is obtained. A step of specifying as a solid region of a specific color; and (c) increasing or decreasing the threshold value using the specific gradation value (0, 255) as an initial threshold value, thereby performing binarization based on the threshold value. The area (S (Tb), S (Tw)) of the pixel set extracted from the solid area of the monochrome image satisfies a predetermined area criterion based on the comparison with the area (Sb, Tw) of the solid area. the threshold value is determined and corrected threshold the threshold value when (DT A step of obtaining as DTw), reset in (d) of the (the correction threshold acquired by the step c) (DTb, the tone value of DTw), the specific tone value (0,255) And a step of adjusting the contrast of the monochrome image.

The invention of claim 9 is a computer-readable program, wherein the computer reads the program, and the CPU of the computer executes the program in a memory, thereby expressing the computer in multi-tone representation. an acquisition means for acquiring data of a monochrome image with, on the basis of the monochrome image, the gradation values within a predetermined tone range with respect to a particular gray scale value corresponding to a specific color (0,255) (0~TMb , TMw to 255) specifying a pixel set as a solid region of the specific color, and increasing or decreasing the threshold using the specific gradation value (0, 255) as an initial threshold , the area of the pixel set is extracted from the solid region of the monochrome image by the binarization by the threshold (S (Tb), S ( Tw)) is, in the solid area Product (Sb, Tw) based on a comparison between, determines the threshold value when satisfying a predetermined area basis, correction threshold the threshold value (DTb, DTw) a correction threshold acquisition means for acquiring as said correction By resetting the gradation values of the threshold values for use (DTb, DTw) to the specific gradation values (0, 255), the image processing apparatus is provided with a contrast adjustment unit that adjusts the contrast of the monochrome image. A program characterized by that.

According to the first to ninth aspects of the present invention, after specifying a solid area of a specific color based on a monochrome image, an area extracted from the solid area using a specific gradation value corresponding to the specific color as an initial threshold value the area, based on a comparison between the area of the solid area, to determine the threshold value when satisfying a predetermined area basis, to the determined threshold value correction threshold, the appropriate correction threshold to the contrast adjustment You can get it. Accordingly, the contrast adjustment of the monochrome image can be executed with high accuracy and efficiency.

  In addition, according to the second aspect of the present invention, it is possible to improve the accuracy of specifying the solid area by making the processing target of the specifying means a smoothed image.

  According to the third aspect of the invention, since the specifying means sets the further contracted area as a solid area, the solid area can be specified effectively.

According to the fourth aspect of the present invention, since the correction threshold is determined from each of the solid areas for the drawing color and the background color, appropriate contrast adjustment can be performed on the monochrome image.

  According to the fifth aspect of the present invention, the solid region specifying threshold value is acquired from each of the gradation side of the drawing color and the gradation side of the background color based on the frequency distribution of the pixels of each gradation. The accuracy of identifying the solid area can be improved.

  According to the sixth aspect of the present invention, the solid area specifying threshold is determined based on the gradation value having the highest appearance frequency on the specific color side and the background color side relative to the intermediate gradation. The area identification accuracy can be improved.

In addition, according to the seventh aspect of the present invention, contrast adjustment is performed with high accuracy by removing, in advance, an edge portion of a monochrome image that is likely to contain noise from a correction threshold acquisition target region by digitization processing or the like. be able to.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described in detail with reference to the accompanying drawings.

<1. Embodiment>
<1.1. Configuration and Function of Image Processing Apparatus 100>
[Schematic configuration]
FIG. 1 is an external view of an image processing apparatus 100 according to an embodiment of the present invention. FIG. 2 is a diagram illustrating a hardware configuration of the image processing apparatus 100.

  The image processing apparatus 100 mainly includes a CPU 10, a storage unit 11, an operation unit 12, a display unit 13, a disk reading unit 14, a communication unit 15, and a scanner 16, and functions as a general computer.

  The CPU 10 operates according to the program 2 stored in the storage unit 11 to execute various data calculations and control signal generation, and controls each component of the image processing apparatus 100. The functional blocks realized by the CPU 10 will be described later.

  The storage unit 11 includes a RAM and a hard disk that serve as a temporary working area of the CPU 10, and a read-only ROM (not shown). The storage unit 11 has a function as a recording medium for storing the program 2 and various data. The program 2 may be transferred from the recording medium 9 to the storage unit 11 via the disk reading unit 14 or may be transferred to the storage unit 11 via the communication unit 15.

  The operation unit 12 is used to input a user instruction to the image processing apparatus 100. That is, the operation unit 12 functions as an input device in the image processing apparatus 100. Specifically, the operation unit 12 corresponds to, for example, a keyboard, a mouse, and various buttons.

  The display unit 13 displays various data as images on the screen. That is, the display unit 13 functions as a display device in the image processing apparatus 100. Specifically, the display unit 13 corresponds to, for example, a CRT monitor or a liquid crystal display, but may have a part of the function of the operation unit 12 like a touch panel display.

  The disk reading unit 14 is a device that reads data stored in the portable recording medium 9 and transfers the data to the storage unit 11. That is, the disk reading unit 14 functions as a data input device in the image processing apparatus 100.

  Note that the image processing apparatus 100 according to the present embodiment includes a CD-ROM drive as the disk reading unit 14. However, the disk reading unit 14 is not limited to this, and may be, for example, an FD drive, a DVD drive, or an MO device. If the disk reading unit 14 has a function of recording data on the recording medium 9, the disk reading unit 14 can substitute a part of the function of the storage unit 11.

  The communication unit 15 has a function for performing communication via the network between the image processing apparatus 100 and another device group (not shown).

  The scanner 16 is a reading device for optically reading an image, has a large number of image sensors, and has a function for acquiring an analog image recorded on a paper medium or the like as digital data.

  FIG. 3 is a diagram illustrating functional blocks of the image processing apparatus 100 together with a data flow. The acquisition unit 21, the region specifying unit 22, the correction threshold acquisition unit 23, and the color tone correction unit 24 illustrated in FIG. 3 are functional blocks that are realized mainly when the CPU 10 operates according to the program 2.

[Acquisition unit 21]
The acquisition unit 21 performs multi-gradation representation (here, 256 gradations (8 bits)) based on a read signal obtained by reading an image recorded on a printing substrate (paper or the like) with the scanner 16. Monochrome image data DI is acquired and stored in the storage unit 11.

  Here, the image to be processed by the image processing apparatus 100 according to the present embodiment may be a digital image digitized in the past in addition to an analog image (original image) described on paper or the like.

  Further, in the present embodiment, the image processing apparatus 100 targets an image (monochrome image I) expressed in monochrome (single color shading). In the present embodiment, the color (drawing color) of a portion corresponding to a drawing element such as a drawing line or a halftone dot in the original image is “black”, and the portion corresponding to the background color of paper (that is, out of a monochrome image) In the following description, it is assumed that the color (background color) is “white”. However, this is defined for convenience of explanation, and the combination of the drawing color and the background color is not limited to this, for example.

  The acquisition unit 21 generates monochrome image data DI in multi-tone representation by performing predetermined processing on the image read by the scanner 16. Here, when the analog image read by the scanner 16 is a color image, or when the digital image digitized in the past is a color image, the acquisition unit 21 discards the extra color information, and the monochrome representation image. Is generated.

[Area specifying unit 22]
The area specifying unit 22 mainly includes a mask threshold value determining unit 221, a smoothing unit 222, and a mask generating unit 223. Based on the monochrome image data DI, the region specifying unit 22 is predetermined for a specific gradation value corresponding to a specific color. A pixel set having gradation values within the gradation range is specified as a solid area of a specific color.

  In general, a solid area of a specific color (for example, black) in an original analog image (original image) is composed of pixels of a plurality of gradations by adding an offset value on a digital image. . Also, the color on the analog image and the color on the digital image do not necessarily match.

  Therefore, the region specifying unit 22 extracts a region that is expected to be solid of a specific color in the original image based on the digital image (monochrome image I), and thus sets the specific gradation value corresponding to the specific color. On the other hand, by setting the predetermined gradation range as an allowable range, an area (solid area) that is highly likely to be solid in the original image is specified.

  In the monochrome image I, the drawing color (black) is expressed on the surface of a predetermined background color (white). Therefore, in the present embodiment, the region specifying unit 22 specifies a region that is expected to be solid of the drawing color (black) and the background color (white) in the original image based on the monochrome image I.

  FIG. 4 is a diagram illustrating the sub-blocks included in the region specifying unit 22 together with the data flow.

  The histogram analysis unit 221 determines the solid region specifying thresholds (black side threshold value TMb and white side threshold value TMw) by analyzing a histogram indicating the frequency of appearance of each gradation pixel of the monochrome image I (histogram analysis). Then, data indicating a solid area specifying threshold value is stored in the storage unit 11. Details of the histogram analysis will be described later.

  The smoothing unit 222 generates smoothed image data DIs by spatially smoothing the monochrome image I. Various methods for smoothing an image have been proposed, and details thereof are omitted here. For example, a pixel calculation is performed using a filter (an averaging filter, a Gaussian filter, or the like).

  By this smoothing process, relatively fine drawing elements (for example, halftone dots and fine lines) included in the monochrome image I are smoothed, so that the region specifying unit 22 selects a solid region in the original image. It is possible to specify a portion having a certain extent (width) as a solid region.

  The mask generation unit 223 mainly includes a binarization unit 2231 and a contraction unit 2232, and based on the solid region specifying threshold value and the smoothed image data DIs, the black solid region mask data DMb and the white solid region mask data DMw. Is generated.

  Specifically, when generating the white solid area mask data DMw, the mask generation unit 223 uses the binarization unit 2231 to convert a pixel set having a gradation value equal to or higher than the white side threshold value TMw of the smoothed image to white (gradation). In the tone value 255), a pixel having a gradation value less than the white threshold TMw is converted to black (gradation value 0).

  On the other hand, when generating the black solid region mask data DMb, the mask generation unit 223 uses the binarization unit 2231 to obtain the gradation values of the pixel set having the gradation value equal to or less than the black side threshold value TMb of the smoothed image. A pixel having a gradation value exceeding the black side threshold value TMb is converted to white (gradation value 255) into black (gradation value 0).

  Further, the contraction unit 2232 executes contraction processing of the pixel set converted into the specific color a predetermined number of times (that is, contracts by a predetermined number of pixels). That is, when generating the white solid region mask data DMw, the white portion of the data obtained by the binarizing unit 2231 is used. When generating the black solid region mask data DMb, the binarizing unit 2231 is used. Each black portion of the obtained data is contracted. Each mask data obtained by contraction is stored in the storage unit 11.

  In this way, the region specifying unit 22 determines appropriate solid region specifying threshold values (white side threshold value TMw, black side threshold value TMb) by the histogram analysis unit 221, thereby generating white in the original image from the smoothed image data DIs. White solid area (corresponding to the white solid area mask data DMw) that is estimated to be a solid color (that is, a plain area), and a black solid area (black solid area mask that is estimated to be a black solid color in the original image) Data DMb).

[Correction Threshold Acquisition Unit 23]
Returning to FIG. 3, the correction threshold value acquisition unit 23 mainly includes an area determination unit 231, and extracts from a specific color solid region using a gradation value selected from the specific color solid region of the monochrome image I as a threshold value. The area of the area to be processed is compared with the area of the solid area of the specific color. By this comparison, the area determination unit 231 determines whether or not the area of the extracted region satisfies a predetermined area criterion, and the gradation value when the predetermined area criterion is satisfied is acquired as a correction threshold value. It is stored in the storage unit 11.

  For example, black in the original image may be converted to a halftone color (gradation value 1 to 254) instead of black (gradation value 0) after digitization. That is, pixels existing in the black solid area of the monochrome image I are likely to be black in the original image even if they are halftone colors, so the gradation value should be corrected to “0”. . Similarly, since the pixel existing in the white solid region of the monochrome image I is likely to be white in the original image, the gradation value should be corrected to “255”.

  From this point of view, in the present embodiment, the correction threshold value acquisition unit 23 performs a binarization process using the selected gradation value (selected gradation value) as a threshold value from a solid area of a specific color of the monochrome image I. The selected gradation value when the ratio of the extracted area (pixel set) to the solid area of the specific color is the majority (for example, 99.9%) is acquired as the correction threshold value.

  In the present embodiment, the correction threshold value acquisition unit 23 acquires a lower limit threshold value TCb and an upper limit threshold value TCw as correction threshold values from each of the black solid region and the white solid region specified as the solid region of the specific color.

[Color tone correction unit 24]
The color tone correction unit 24 corrects the color tone of the monochrome image I based on the correction threshold acquired by the correction threshold acquisition unit 23. In the present embodiment, the gradation value distribution range between the upper limit threshold value TCw and the lower limit threshold value TCb is extended to the high gradation side and the low gradation side according to a predetermined rule based on the histogram for the monochrome image I. Thus, the color tone of the monochrome image is corrected.

  The above is the description of the configuration and functions of the image processing apparatus 100. Next, the operation of the image processing apparatus 100 will be described.

<1.2. Operation of Image Processing Device 100>
FIG. 5 is a flowchart showing the operation of the image processing apparatus 100. The following operations are realized by the control of the CPU 10 unless otherwise specified.

  The image processing apparatus 100 acquires monochrome image data DI after performing predetermined initial settings (step S1). As described above, the monochrome image data DI is acquired by the acquisition unit 21 based on the reading of the analog image by the scanner 16. The monochrome image data DI may be data that has been digitized in the past. In this case, the monochrome image data DI is acquired via the recording medium 9 or the like, or acquired via a network.

  FIG. 6 is a diagram illustrating an example of the monochrome image I represented by the monochrome image data DI. The original image of the monochrome image I shown in FIG. 6 is a black drawing color on a paper having a white background color, a curve or a straight line is drawn, is solid, or a halftone dot (dots and diagonal lines in FIG. 6). Is a pasted image. Therefore, an image obtained by reading with the scanner 16 should ideally be expressed in black and white. However, since an unexpected addition of an offset component occurs, the monochrome image I is an image having a gray color (halftone color) as a whole. The image processing apparatus 100 acquires an image (corrected image Im) corrected to an ideal state by sequentially executing the following operations on such a monochrome image I.

  Returning to FIG. 5, when the acquisition of the monochrome image data DI is completed, the image processing apparatus 100 specifies a solid area (a white solid area and a black solid area) of a specific color based on the monochrome image I (step S <b> 2). . The detailed operation of step S2 will be described with reference to FIG.

  FIG. 7 is a flowchart showing details of the operation of the image processing apparatus 100 in specifying the solid area.

[Histogram analysis]
When the identification of the solid area is started, the image processing apparatus 100 analyzes the histogram for the monochrome image data DI (step S21). Specifically, the histogram analysis unit 221 calculates the appearance frequency of each gradation pixel included in the monochrome image I.

  Here, the analysis target of the histogram analysis unit 221 may be the entire monochrome image I, but in the present embodiment, the edge portion (edge region ER) having a predetermined pixel width is excluded from the entire region of the monochrome image I. The remaining area RR (area surrounded by a broken line in FIG. 6) is set.

  That is, noise or the like is particularly likely to occur at the edge portion of the acquired monochrome image I due to a reading error in the scanner 16, and therefore, in the present embodiment, from the remaining area RR in the entire area of the monochrome image I. The solid area of a specific color is specified. Accordingly, the histogram analysis is also performed for the remaining region RR. In this way, the tone correction can be performed with high accuracy by removing the edge region ER that easily includes noise from the correction threshold acquisition target region in advance.

  Note that not all the edge portions of the four sides of the monochrome image I have to be removed, and for example, a part of the removed region may be removed. The pixel width to be removed may be determined according to the distance at which a drawing element such as a drawing line (drawing color pixel) is detected from the edge of the monochrome image I toward the center.

  FIG. 8 is a histogram relating to the gradation values of the monochrome image I shown in FIG. In the histogram shown in FIG. 8, the series on the horizontal axis is the gradation value (0 to 255), and the frequency on the vertical axis is the frequency of appearance of the pixels.

  Generally, in a histogram of a digital image generated from a line drawing expressed in black and white, as shown in FIG. 8, the white background color gradation (= 255) side and the black drawing color gradation (= There is a tendency that a peak (peak) of the appearance frequency appears on the (0) side.

  Therefore, in the present embodiment, the histogram analysis unit 221 uses a gradation (intermediate gradation: here) between the gradation of the background color (gradation value 255) and the gradation of the drawing color (gradation value 0). On the gradation side of the drawing color (left side in FIG. 8) than the gradation value 127), a predetermined value is applied to the gradation side of the background color (right side in FIG. 8) with respect to the gradation value TPb having the highest appearance frequency. A gradation value (= TPb + X) biased by the number of classes X is acquired as the black side threshold value TMb (step S22).

  In the same manner, the histogram analysis unit 221 uses the drawing color for the gradation value TPw having the highest appearance frequency on the gradation side of the background color (right side in FIG. 8) with respect to the intermediate gradation. A gradation value (= TPw−X) biased by a predetermined number of classes X toward the gradation side (left side in FIG. 8) is acquired as the white side threshold value TMw (step S22).

  In this way, tone values that are further biased inward by a predetermined number of classes X with respect to the tone values TPb and TPw of the right and left peaks of the histogram are acquired as the black side threshold value TMb and the white side threshold value TMw. As a result, it is possible to improve the accuracy of specifying the black solid area and the white solid area that are expected to be black or white solid in the original image.

  Note that if the value of the class number X is too large, a region that is not solid in the original image may be erroneously determined as a solid region. Therefore, the value of the class number X is preferably set according to the style of the original image, the performance of the scanner 16, and the like. In the present embodiment, the value of the class number X is about “10”, but this is merely an example, and can be changed as appropriate.

  In the present embodiment, the amount shifted from each frequency peak (class number X) is matched between the case where the black side threshold value TMb is determined and the case where the white side threshold value TMw is determined. It may be set.

  Returning to FIG. 7, when the solid region specifying thresholds (black side threshold value TMb, white side threshold value TMw) are obtained by histogram analysis, the smoothing unit 222 smoothes the monochrome image I by spatially smoothing. Image data DIs is generated (step S23).

  When the smoothed image data DIs is generated, the image processing apparatus 100 causes the mask generation unit 223 to generate the black solid area mask data DMb and the white color based on the smoothed image data DIs and the black side threshold value TMb and the white side threshold value TMw. Solid area mask data DMw is generated (steps S24 and S25).

  Specifically, in order to generate the black solid region mask data DMb in step S23, the mask generation unit 223 has, for each pixel of the smoothed image data DIs, a gradation equal to or lower than the black side threshold value TMb acquired in step S22. All pixel sets of values are converted to black (= gradation value 0), and all pixel sets having gradation values exceeding the black side threshold value TMb are converted to white (= gradation value 255). More specifically, this extraction process is executed by a binarization process based on the black side threshold value TMb of the binarization unit 2231 (step S24).

  Further, for the area obtained by the binarization process, the black solid area mask indicating the area information in which the black pixel set is contracted by a predetermined number of pixels (for example, 7 pixels) by the contraction process of the contraction unit 2232 (step S25). Data DMb is generated.

  Further, in order to generate the white solid region mask data DMw, the mask generation unit 223 sets all the pixels of the gradation value equal to or higher than the white side threshold value TMw acquired in step S22 among the pixels of the smoothed image data DIs to white. (= Gradation value 255) and all pixels having gradation values not exceeding the white side threshold value TMw are converted to black (= gradation value 0). This binarization process is executed by the binarization unit 2231 (step S24).

  Further, for the obtained image data, white solid area mask data DMw indicating area information obtained by contracting a white pixel set by a predetermined number of pixels (for example, 7 pixels) by the contraction processing of the contraction unit 2232 (step S25). Generated.

  FIG. 9 is a diagram showing images IMb and IMw of each mask data acquired from the monochrome image I shown in FIG. Note that the black portion in the image IMb shown in FIG. 9 indicates a black solid region extracted from the smoothed image, and the white portion in the image IMw indicates a white solid region extracted from the smoothed image. Show.

  As shown in FIG. 9, in the image IMb (corresponding to the black solid area mask data DMb), relatively thin outlines (black drawing lines), halftone dots, etc. in the monochrome image I shown in FIG. Only a black solid portion (such as a triangle) that has been removed by processing is extracted as a black region.

  Further, in the image IMw (corresponding to the white solid area mask data DMw), the white solid area of the background is mainly extracted as a white area in the monochrome image I shown in FIG.

  The image processing apparatus 100 appropriately refers to the black solid area mask data DMb and the white solid area mask data DMw when executing correction threshold (lower threshold TCb, upper threshold TCw) determination processing described later.

  Note that, in the smoothed image obtained by the smoothing process in step S23, noise components included in the image, fine halftone dots, and portions expressed by relatively fine lines are spatially smoothed. In step S23, a solid area of a specific color is specified from the smoothed image. Therefore, since an area having a certain width is specified as a solid area, it is possible to effectively specify an area that is very likely to be a solid of a specific color in the original image.

  Returning to FIG. 5 again, when the black solid region and the white solid region are specified, the image processing apparatus 100 corrects the threshold values for color tone correction (lower threshold TCb, upper threshold TCw) in each solid region of the monochrome image I. Is determined (step S3). Details of the operation of the image processing apparatus 100 in step S3 will be described with reference to FIGS.

  FIG. 10 is a flowchart showing details of the operation of the image processing apparatus 100 in the determination process of the lower limit threshold value TCb. FIG. 11 is a flowchart showing details of the operation of the image processing apparatus 100 in the determination process of the upper limit threshold value TCw.

  First, as shown in FIG. 10, when the determination process of the lower limit threshold value TCb is started, the correction threshold value acquisition unit 23 temporarily sets the threshold value Tb to 0 (= black tone value) as an initial value (step S31). . Then, the correction threshold value acquisition unit 23 binarizes the monochrome image I based on the threshold value Tb (= 0) (step S32).

  Specifically, a pixel having a gradation equal to or lower than the threshold Tb is converted to black (gradation value 0), and a pixel having a gradation exceeding the threshold Tb is converted to white (gradation value 255). Then, by comparing the binarized image with the black solid area mask data DMb, a pixel set included in the black solid area is extracted from the black pixels of the binarized image. This process is equivalent to extracting a pixel set whose gradation value is equal to or less than the threshold value Tb from the black solid region of the monochrome image I.

  Then, the correction threshold value acquisition unit 23 counts the number of pixels extracted in step S32 (step S33), and calculates an area S (Tb) of a pixel set having a gradation value equal to or less than the threshold value Tb in step S31. .

  Furthermore, the area determination unit 231 compares the area S (Tb) of the pixel set with the area Sb of the black solid region. Then, it is determined whether or not the ratio of the area of the pixel set having the gradation value equal to or smaller than the threshold value Tb to the black solid region is equal to or greater than a predetermined reference value t (step S34).

  In step S34, when it is determined that the ratio (area ratio) of the relative area is less than the reference value t with the set threshold value Tb (NO in step S34), the correction threshold value acquisition unit 23 sets the threshold value Tb. A value obtained by adding “1” to the threshold value Tb (here, gradation value 1) is reset to the threshold value Tb (step S35), and the processing after step S32 is executed again.

  On the other hand, when it is determined that the area ratio is greater than or equal to the reference value t (YES in step S34), the correction threshold value acquisition unit 23 stores the threshold value Tb set at that time as the lower limit threshold value TCb. 11 (step S36), and the determination process of the lower limit threshold value TCb is terminated.

  As shown in FIG. 11, when the correction threshold value acquisition unit 23 starts the determination process of the upper limit threshold value TCw, the threshold value Tw is temporarily set to 255 (white gradation value) as an initial value (step S31a). Then, the correction threshold value acquisition unit 23 binarizes the monochrome image I based on the temporarily set threshold value Tw (step S32a).

  Specifically, the gradation value of a pixel having a gradation equal to or higher than the threshold Tw is converted to white (gradation value 255), and the gradation value of a pixel having a gradation less than the threshold Tw is converted to black (gradation value 0). ). Then, by comparing this binarized image with the white solid area mask data DMb, a pixel set included in the white solid area is extracted from the white pixels of the binarized image. This process is equivalent to extracting pixels having a gradation value equal to or greater than the threshold value Tw from the white solid region of the monochrome image I.

  Then, the correction threshold value acquisition unit 23 counts the number of pixels extracted in step S32a (step S33a), and calculates an area S (Tw) of a pixel set having gradations equal to or higher than the threshold value Tw set in step S31a.

  Further, the area determination unit 231 compares the area S (Tw) of the pixel set with the area Sw of the white solid area, so that the ratio of the relative area in the black solid area of the pixel set is a predetermined reference value. It is determined whether it is t or more (step S34a).

  In step S34a, when it is determined that the ratio of the relative area does not reach the reference value t with the set threshold value Tw (NO in step S34a), the correction threshold value acquisition unit 23 sets the set threshold value Tw (here, , Gradation value 255), a value obtained by subtracting “1” (in this case, gradation value 254) is reset to threshold value Tw (step S35a), and the processing after step S32a is executed again.

  On the other hand, when it is determined that the area ratio is equal to or greater than the reference value t (YES in step S34a), the correction threshold value acquisition unit 23 stores the threshold value Tw set at that time as the upper limit threshold value TCw. 11 (step S36a) and the determination process of the upper limit threshold value TCw ends.

  In steps S34 and S34a, the threshold value Tb when it is determined that the pixel set having the gradation value equal to or smaller than the (selected) threshold value, or the above gradation value occupies most of the area of each solid region. In this embodiment, the value of the reference value t is set to t = 0.999. However, this is merely an example and can be changed as appropriate.

  In the present embodiment, the determination criteria (reference value t) for the area ratio are matched between the case where the lower limit threshold value TCb is determined and the case where the upper limit threshold value TCw is determined. Good.

  The above is the detailed operation of the correction threshold (lower threshold TCb, upper threshold TCw) determination process.

  Returning to FIG. 5 again, when the correction threshold value is determined, the color tone correction unit 24 corrects the color tone of the monochrome image I based on the lower limit threshold value TCb and the upper limit threshold value TCw (step S4), and acquires corrected image data DIm. . The tone correction process will be described with reference to FIG.

  FIG. 12 is a histogram relating to the gradation values of the corrected image Im after the color tone correction processing.

  In the present embodiment, the color tone correction unit 24 converts the gradation value to “255” for pixels with gradations equal to or higher than the upper threshold TCw, and converts the gradation value to “0” for pixels with gradations equal to or lower than the lower threshold TCb. To do. Then, as shown in FIG. 12, the color tone correction unit 24 has a frequency distribution (shown by hatching) before the color tone correction for the gradation pixel between the lower limit threshold value TCb and the upper limit threshold value TCw that is minimum after the color tone correction. The gradation value of each pixel is converted so as to be distributed in the range of gradation value 0 to maximum gradation value 255.

  By performing such color tone correction, the shape of the histogram between the upper limit threshold value TCw and the lower limit threshold value TCb is evenly expanded to the left and right (see FIG. 12). In other words, the image processing apparatus 100 performs contrast adjustment by setting a highlight point as the upper limit threshold value TCw and a shadow point as the lower limit threshold value TCb.

  Note that the technique for extending the distribution range for (part of) the histogram depends on, for example, the correction threshold determined in step S3 and the distribution range after color correction (here, 0 to 255). The image processing apparatus 100 may be configured to automatically create a lookup table and refer to the lookup table as appropriate to perform gradation value conversion of each pixel.

  In the present embodiment, the color correction is performed by expanding the entire frequency distribution between the correction thresholds. For example, in the frequency distribution between the lower threshold TCb and the upper threshold TCw, Alternatively, only a part such as a hem part on one side may be expanded. Further, the size of this part may be specified by the operator.

  FIG. 13 is a diagram showing a corrected image Im obtained by the color tone correction process for the monochrome image I shown in FIG. As shown in FIG. 13, according to the line drawing processing apparatus 100, the offset component is removed from the monochrome image I shown in FIG. 6 without erasing the black solid portion or the pattern attached to the figure, and A corrected image Im having an appropriate contrast can be acquired.

  In the image processing apparatus 100 according to the present embodiment, a solid region of a specific color is identified based on the monochrome image I obtained by reading an original image with the scanner 16, and the threshold value when the area ratio to the solid region satisfies the reference value t is set. Based on this, a correction threshold is determined. Since the image processing apparatus 100 executes color tone correction based on the correction threshold value, the image processing apparatus 100 can acquire a corrected image Im that is faithful to the original image. Therefore, a digital image suitable for purposes such as colorization (coloring) and reprinting (duplication) can be acquired from an analog image.

  Further, according to the image processing apparatus 100, since the operator only needs to perform predetermined initial settings, the image processing (color tone correction) of the monochrome image I can be performed efficiently.

<2. Modification>
As mentioned above, although embodiment of this invention has been described, this invention is not limited to the said embodiment, A various deformation | transformation is possible.

  For example, in the above-described embodiment, it has been described that the image processing apparatus 100 acquires the lower limit threshold value TCb and the upper limit threshold value TCw and corrects the color tone of the monochrome image I. However, the configuration of the image processing apparatus 100 is not limited to this. For example, a black solid region is specified, only the lower limit threshold value TCb is acquired, and color tone correction is performed based only on the lower limit threshold value TCb. It may be. That is, the image processing apparatus 100 may be configured to perform color tone correction while paying attention only to a specific color (drawing color or background color) included in the monochrome image I.

  In the above embodiment, when determining the correction threshold values (lower threshold value TCb, upper threshold value TCw), the initial values of the threshold values Tb and Tw are set to the black gradation value (gradation value 0) or the white gradation value (scale). As the tone value 255), gradation values satisfying the area standard are sequentially detected while being shifted one class at a time. However, the method for acquiring the correction threshold value is not limited to this. For example, a threshold value (gradation value) that satisfies the area criterion may be detected from the range of gradation values included in each solid region of the monochrome image I.

  Moreover, although each functional block shown in the said embodiment is implement | achieved by software, you may implement | achieve part or all of these functional blocks as hardware by a dedicated logic circuit.

  Furthermore, each structure demonstrated in the said embodiment and each modification can be suitably combined unless it mutually contradicts.

1 is an external view of an image processing apparatus according to an embodiment of the present invention. It is a figure which shows the hardware constitutions of an image processing apparatus. It is a figure which shows the functional block of an image processing apparatus with the flow of data. It is a figure which shows the subblock with which an area | region specific part is provided with the flow of data. It is a flowchart which shows operation | movement of an image processing apparatus. It is a figure which shows an example of the monochrome image which monochrome image data expresses. It is a flowchart which shows the detail of operation | movement of the image processing apparatus in specification of a solid area | region. 7 is a histogram relating to the gradation value of the monochrome image shown in FIG. 6. It is a figure which shows the image of each mask data acquired from the monochrome image shown in FIG. It is a flowchart which shows the detail of operation | movement of the image processing apparatus in the determination process of a lower limit threshold value. It is a flowchart which shows the detail of operation | movement of the image processing apparatus in the determination process of an upper limit threshold value. It is a histogram regarding the gradation value of the correction image after a color tone correction process. It is a figure which shows the correction image obtained by the color tone correction process about the monochrome image shown in FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Image processing apparatus 2 Program 21 Acquisition part 22 Area | region specific part 221 Histogram analysis part 222 Smoothing part 223 Mask generation part 2231 Binarization part 2232 Shrinkage part 23 Correction threshold acquisition part 231 Area determination part 24 Color tone correction part DI Monochrome image Data DIm Corrected image data DIs Smoothed image data DMb Black solid area mask data DMw White solid area mask data I Monochrome image Im Corrected image RR Residual area ER Edge area TCb Lower threshold TCw Upper threshold TMb Black threshold TMw White threshold t Standard value

Claims (9)

An image processing apparatus for adjusting a contrast of a monochrome image,
Acquisition means for acquiring monochrome image data in multi-tone representation;
Based on the monochrome image, a pixel set of gradation values (0 to TMb, TMw to 255) within a predetermined gradation range with respect to a specific gradation value (0, 255) corresponding to a specific color is assigned to the specific color. A specifying means for specifying as a solid area;
By using the specific gradation value (0, 255) as an initial threshold value, and increasing or decreasing the threshold value, an area of a pixel set extracted from the solid area of the monochrome image by binarization using the threshold value The threshold when (S (Tb), S (Tw)) satisfies a predetermined area criterion is determined based on the comparison with the area (Sb, Tw) of the solid region, and the threshold is corrected. Correction threshold value acquisition means for acquiring (DTb, DTw) ;
Contrast adjustment means for adjusting the contrast of the monochrome image by resetting the gradation values of the correction threshold values (DTb, DTw) to the specific gradation values (0, 255) ;
An image processing apparatus comprising: The image processing apparatus according to claim 1,
Smoothing means for generating a smoothed image by spatially smoothing the monochrome image;
Further comprising
The specifying means is:
An image processing apparatus that identifies the solid region based on the smoothed image. The image processing apparatus according to claim 1, wherein:
The specifying means is:
An image processing apparatus characterized in that an area obtained by further shrinking the pixel set of gradation values is specified as the solid area. The image processing apparatus according to any one of claims 1 to 3,
The specifying means is:
Based on the monochrome image, a pixel set having a gradation value within a predetermined gradation range with respect to the gradation value corresponding to the drawing color is specified as the first solid area, and the gradation value corresponding to the background color is determined. A pixel set of gradation values within a predetermined gradation range is specified as the second solid area,
The correction threshold acquisition means includes
Obtaining a first correction threshold and a second correction threshold as the correction threshold for each of the first solid area and the second solid area of the monochrome image;
The contrast adjusting means includes
An image processing apparatus comprising: adjusting contrast of the monochrome image based on the first correction threshold and the second correction threshold. The image processing apparatus according to claim 4,
The specifying means is:
By analyzing the frequency distribution of the pixels of each gradation value of the monochrome image, the first solid image is determined based on the solid area specifying threshold values acquired from the gradation side of the drawing color and the gradation side of the background color. An image processing apparatus that identifies an area and the second solid area. The image processing apparatus according to claim 5,
The specifying means is:
With respect to the gradation value having the highest appearance frequency on the gradation side of the drawing color from the intermediate gradation between the gradation of the drawing color and the gradation of the background color, a predetermined value is applied to the gradation side of the background color. The first gradation value biased by the number of classes,
A second gradation value biased by a predetermined class number toward the gradation side of the drawing color with respect to the gradation value having the highest appearance frequency on the gradation side of the background color from the intermediate gradation;
Are set as the solid region specifying threshold values. The image processing apparatus according to any one of claims 1 to 6,
The specifying means is:
An image processing apparatus, wherein the solid area is specified from a remaining area excluding an edge portion having a predetermined pixel width in the entire area of the monochrome image. An image processing method for adjusting contrast of a monochrome image,
(a) acquiring monochrome image data in multi-tone representation;
(b) Based on the monochrome image acquired in the step (a), the gradation value (0 to TMb, 0 to TMb, within a predetermined gradation range with respect to the specific gradation value (0, 255) corresponding to the specific color . TMw˜255) pixel set as a solid region of the specific color;
(c) Pixels extracted from the solid area of the monochrome image by binarization using the threshold by setting the specific gradation value (0, 255) as an initial threshold and increasing or decreasing the threshold. Based on the comparison of the area (S (Tb), S (Tw)) of the set with the area (Sb, Tw) of the solid region , the threshold value when the predetermined area criterion is satisfied is determined, and the threshold value is determined. Acquiring as correction threshold values (DTb, DTw) ;
(d) By resetting the gradation value of the correction threshold value (DTb, DTw) acquired in the step (c) to the specific gradation value (0, 255), the monochrome image is contrasted. Adjusting , and
An image processing method comprising: A computer-readable program,
Acquisition means for acquiring monochrome image data in multi-tone representation by causing the computer to read the program and causing the CPU of the computer to execute the program in a memory;
Based on the monochrome image, a pixel set of gradation values (0 to TMb, TMw to 255) within a predetermined gradation range with respect to a specific gradation value (0, 255) corresponding to a specific color is assigned to the specific color. A specifying means for specifying as a solid area;
By using the specific gradation value (0, 255) as an initial threshold value, and increasing or decreasing the threshold value, an area of a pixel set extracted from the solid area of the monochrome image by binarization using the threshold value The threshold when (S (Tb), S (Tw)) satisfies a predetermined area criterion is determined based on the comparison with the area (Sb, Tw) of the solid region, and the threshold is corrected. Correction threshold value acquisition means for acquiring (DTb, DTw) ;
Contrast adjustment means for adjusting the contrast of the monochrome image by resetting the gradation values of the correction threshold values (DTb, DTw) to the specific gradation values (0, 255) ;
A program for causing a computer to function as an image processing apparatus.